Loading packages

library(tidyverse)
library(sf)
library(leaflet)
library(htmltools)
library(htmlwidgets)
library(RColorBrewer)

Loading data

First, I will import a set of points representing visited/resided buildings of probable/confirmed COVID-19 cases in the past 14 days (28 days if with cluster). I will convert the coordination system to WGS84.

covid <- st_read("CHP_BUILDING_COVID19_20201023.geojson")
## Reading layer `CHP_BUILDING_COVID19_20201023' from data source `E:\Github\mengyao_li-vis\CHP_BUILDING_COVID19_20201023.geojson' using driver `GeoJSON'
## Simple feature collection with 107 features and 12 fields
## geometry type:  POINT
## dimension:      XY
## bbox:           xmin: 809968 ymin: 809225 xmax: 846100 ymax: 840233
## projected CRS:  Hong Kong 1980 Grid System
covid <- covid %>%
  st_transform(crs = 4326)

I will also import a set of polygons representing all districts of Hong Kong with their populations density information.

districts <- read_sf(dsn = ".", layer = "Hong_Kong_Mid_Year_Population_Density_in_2018")
names(districts)[5] <- "pop_density"

Displaying points and polygons on a Leaflet map

Now I will draw the points on a leaflet map so we can pan around and zoom in on the parts of Hong Kong where we want to see the buildings in more detail.

Points as markers

I will start by showing the points as markers. It looks less messy after zooming in.

covid_map1 <- leaflet(districts) %>%
  addProviderTiles(providers$OpenStreetMap) %>%
  addPolygons(fillColor = "grey", stroke = FALSE) %>%
  addMarkers(data = covid,
             popup = ~BLDGNAME_EN) %>%
  addControl("Visited/resided buildings of probable/confirmed COVID-19 cases in the past 14 days", position = "topright") %>%
  addControl('<a href = "https://geodata.gov.hk/gs/view-dataset?uuid=ab290617-f93b-416e-a00d-114566a7783a&sidx=0">Data source</a>',
             position = "bottomleft")

covid_map1

Points as circles

It might look cleaner to show the points as little circles. I have learned how to cluster points from Jiwon.

pal <- colorNumeric(
  palette = "YlOrRd",
  domain = districts$pop_density)

covid_map2 <- leaflet(districts,
                      options = leafletOptions(minZoom = 11, maxZoom = 15)) %>%
  addProviderTiles("Esri.WorldGrayCanvas") %>%
  addPolygons(color = ~pal(pop_density), stroke = FALSE, fillOpacity = 0.3, 
              highlightOptions = highlightOptions(fillColor = "black", fillOpacity = 0.5),
              label = districts$HKDistri_1,
              popup = paste("Population Density: ", format(districts$pop_density, big.mark = ","), "persons per sq.km")) %>%
  
  addCircleMarkers(data =covid,
             fillColor = "red", color = "red",
             stroke = FALSE, radius = 20,
             label = "COVID-19 has been here",
             popup = paste("Building Name: ", covid$BLDGNAME_EN, "<br/>",
                           "Related Case Number: ", covid$RELATEDCASESNO),
             clusterOptions = markerClusterOptions()) %>%
  
  setMaxBounds(lng1 = 113,
               lat1 = 22,
               lng2 = 115,
               lat2 = 23) %>%
  addControl("Visited/resided buildings of probable/confirmed COVID-19 cases in the past 14 days", position = "topright") %>%
  addControl('<a href = "https://geodata.gov.hk/gs/view-dataset?uuid=ab290617-f93b-416e-a00d-114566a7783a&sidx=0">Data source</a>',
             position = "bottomleft")

covid_map2

Saving a separate html file

I can use the saveWidget() function to save any of my leaflet maps as in its own html file.

saveWidget(covid_map2, file = "covid buildings.html")